Small business=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.
0%from 0% in September 2026
Inside the floor by 13 pointsRank 91 → 97 of 97
3 categories · RankedMonster
43Judge labels
0First choices
35Negative labels
14 / 14Models named it
3Categories
October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10.7, every buyer segment counted.
Best standing
0% in Job advertising for mid-market buyers
Rank 110 of 111 in the mid-market standingcriticized challenger
0 of 14 models made it the first choice on the direct prompt; 64% of its 14 labels there were negative.
What the models named instead of Monster →By buyer segmentRead the same way at every buyer size.
Small business102 of 102
0%8 labels
under the label threshold
Mid-market110 of 111
0%14 labels
criticized challenger
Enterprise92 of 92
0%14 labels
criticized challenger
In job advertising · each standing computed within its segment · bars are 0 to 100 · the accent bar is the product's own best reading
Standing by category
Every category where a model named Monster for a mid-market B2B company. Share is first choices across the direct, paraphrase, budget and scale prompts; rank is within every product named in that category.
| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Job advertising and distribution | Talent acquisition | 0% | 110 of 111 | 64% | 14 | criticized challenger | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. |
| Recruitment marketing and career sites | Talent acquisition | 0% | 102 of 104 | 100% | 2 | under 10 labels · led by Teamtailor at 23% | newNew since September 2026: not ranked then, 0% now. |
| Staffing agency platforms | Talent acquisition | 0% | 78 of 136 | 0% | 1 | under 10 labels · led by Zoho Recruit at 22% |
Movement
Since September 2026, Monster held within the floor in all three categories: no change cleared 13 points.
Best category · Job advertising · by segment
Mid-market=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.
0%from 0% in September 2026
Inside the floor by 13 pointsRank 106 → 100 of 103
Enterprise=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.
0%from 0% in September 2026
Inside the floor by 13 pointsRank 64 → 89 of 89
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Job advertising | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 106 → 110 of 111 |
| Recruitment marketing | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 102 of 104, unchanged |
| Staffing agency tools | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 78 of 136, unchanged |
Shares here are read over the models both editions asked, so they can differ by a point or two from the standing above, which counts every model in this edition.
The floor is 13 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured · The editions
By model
How each model treated Monster across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.ShowHide
By model
How each model treated Monster across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
ShowHide| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 0 | 0 | 0 | 1 | 1 |
| GPT-5.4 mini | 0 | 0 | 1 | 0 | 1 |
| Gemini 3.5 Flash | 0 | 0 | 1 | 1 | 2 |
| Perplexity Sonar | 0 | 0 | 1 | 0 | 1 |
| Grok 4.1 Fast | 0 | 1 | 0 | 1 | 2 |
| Mistral Small | 0 | 0 | 0 | 1 | 1 |
| DeepSeek V4 Flash | 0 | 0 | 0 | 1 | 1 |
| Llama 4 Maverick | 0 | 0 | 0 | 0 | 0 |
| Qwen 3.7 Flash | 0 | 0 | 0 | 1 | 1 |
| Kimi K2 | 0 | 0 | 1 | 1 | 2 |
| GLM 4.7 FlashX | 0 | 0 | 0 | 1 | 1 |
| MiniMax M2.5 | 0 | 0 | 1 | 1 | 2 |
| GPT-6 Luna | 0 | 0 | 0 | 0 | 0 |
| Muse Glimmer 30B | 0 | 0 | 0 | 2 | 2 |
By framing
Which of the six questions produced the naming. By model says how often; this says asked what. The first-choice count on the right carries the marks of the models that produced it.
FramingLabels by classFirst choices
Direct0 labelsNone
Paraphrase0 labelsNone
Comparative13 labelsNone
Budget-constrained1 labelNone
Scale-constrained0 labelsNone
Negative29 labelsNone
First choiceAlternativeMentionNegative43 labels in all, every segment counted; 0 of the 0 first choices count toward share, since the comparative and negative framings do not. The bar is one segment per label class, to scale within the framing.
What the models said for it
Verbatim evidence the judge attached to positive labels.
“Stick to vetted alternatives: ... Monster, CareerBuilder” Grok 4.1 Fast · Job advertising · negative prompt · alternative
And against it
Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.
“Frequently cited as generating excessive spam/recruiter calls” Kimi K2 · Job advertising · negative prompt · hard negative
“"Do not post a job opening on Monster.Com."” Muse Glimmer 30B · Recruitment marketing · negative prompt · hard negative
“scammers post fake job listings on real job boards like Indeed, LinkedIn, Monster, Glassdoor, and CareerBuilder” Claude Haiku 4.5 · Job advertising · negative prompt · soft negative
“relying on them for *active marketing* is often considered a mistake compared to modern CRMs” Qwen 3.7 Flash · Recruitment marketing · negative prompt · soft negative
Named alongside
The products named in the same answers as Monster, over the 43 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Monster was named but was not.ShowHide
Named alongside
The products named in the same answers as Monster, over the 43 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Monster was named but was not.
ShowHideProductSame answerTook the first choice insteadHead to head
A head-to-head page exists where both products are among a category's top eight. The other rows are the same fact without a page behind them, so they link to the product instead.
What carried it into the answer
The sites and pages cited by the answers that named Monster. A fact about retrieval, not a lever on the model.
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 41 of the 43 answers that named Monster and are not a share of its labels.
Domains cited
firsthr.app20
noon.ai19
g2.com15
linkedin.com14
hr-ai-index.com12
pin.com11
money.com10
bestjobsearchapps.com9
guideflow.com8
hrtechsaas.com8
126 of the 126 domain citations in answers naming Monster came from somebody else's page.
Pages cited
Pages are listed as the models cited them.
Search and answers
monster.com is not in Google's top ten for any of the category's searches. In the answers, Monster takes 0% of first choices and JobTarget takes 23%.ShowHide
Search and answers
monster.com is not in Google's top ten for any of the category's searches. In the answers, Monster takes 0% of first choices and JobTarget takes 23%.
ShowHideIn search
Google, US estimatesPosition for “job advertising platforms”
–
not in the top ten
Position for “programmatic job advertising platform”
–
not in the top ten
- Searches for its name, Google
- 550,000 a month (“monster”)
- AI search demand for its name, est.
- 400,754 a month
- Organic visits to its site
- about 6,076,226 a month
- Searches its site ranks for
- 343,461 · 9,350 in the top three
- Sites linking to it
- 54,164
- Paid Google search
- 72 searches its ads show for, about 786 clicks and $1,061 a month (estimate)
In answers
This editionShare of first choices
0%
rank 110 of 111 in job advertising
Segment leader
23%
JobTarget
- First choices
- 0 across its categories
- Named in
- 43 answers
- Its own site cited
- in 41 of the answers that named it
Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.
Follow Monster
An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.
Already following? Everything you follow, with a stop for each.
The company
Monster is its own company.ShowHide
The company
Monster is its own company.
ShowHideIn its own words
Stated by the vendor, not checked- Positioning
- Smarter Job Search Tools. Better Results.
- For
- Job seekers and employers
- Free plan or trial
- Upload your resume for free monster.com
- Not stated on the pages read
- Price, starting price, integrations, certifications, hosting, customers
What Monster's own pages state, read September 28, 2026: monster.com. A claimed page can correct any of them.
Is this your product?
Claim this page
Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when Monster's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as Monster, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
What a new claim receivesHide what a new claim receives
A new claim receives the current edition's vendor brief for Monster by email, built from the raw record of the edition. It shows:
- where Monster is named, by buyer and by framing, and which cells hold its first choices;
- the claims the models make when they name it, ranked, with the strongest and the weakest quoted;
- its vocabulary against the segment leader's, and the pages the models cited;
- who was chosen in the answers that did not name Monster, and every reason the record gives;
- a battlecard for each top rival: the head-to-head split, why they win, and the reservation quoted against them;
- one page of published figures cleared to show a buyer.